Driving is a risky and demanding activity in which a person is constantly called upon to avoid potential threats and hazards. Hazard avoidance, a learned behavior, relies upon a number of underlying visual and perceptual processes that must be accomplished in a timely and effective manner. Persons skilled in the art distinguish the detection of objects in and near one's travel path, recognition of which objects pose the greatest potential threats, the fixation of attention upon the highest priority safety threats, and attention shifting between those safety threats, on a dynamic and continuous basis, as a minimum set of activities that must be accomplished to exercise proper vehicle control to avoid hazards while driving. A driver characteristic signifying the proficient performance of these activities, in the aggregate, is referred to herein as “expert search and scanning skills,” or ‘ES3.’
Drivers who are legally operating their vehicles may exhibit ES3 deficits either because of impairment resulting from the onset of acute or chronic medical conditions or diseases, or more advanced stages of normal human aging; or because of inexperience with the driving task, as is the case with young, novice drivers who have not yet fully learned which objects deserve priority as potential threats. It may be demonstrated that skills lost due to impairment, or not fully learned due to inexperience, can be improved through training.
Research by Government agencies and by non-profit organizations has produced “model” curricula for driver training. When addressing crash avoidance, such model curricula consistently emphasize the importance of visually searching and scanning the scene while driving, rapidly directing and re-directing attention to recognized safety threats to anticipate the need to adjust speed or to maneuver the vehicle before a routine response becomes an emergency. Effective and affordable tools for measuring proficiency in such visual search and scanning skills are presently lacking.
To date, the training and assessment of driver's visual search and scanning skills that takes place outside of an actual car (or high-fidelity driving simulator) has employed either (1) static images (including drawings, diagrams, photographs, and slides); (2) computer graphics images; or (3) film or video images of roadway scenes. The limitations of the first two categories include, respectively, the absence of the dynamic qualities of moving traffic; and a “cartoonish” image quality that does not faithfully represent the appearance or the dynamic qualities of real-world threats and hazards encountered while driving. The limitations of the third category include the nature of the driver's involvement with the training process, characterized either by (1) passively watching (and not interacting with) the training materials, or (2) interacting with the film or video images based on a memory of what was seen instead of on a “real time” basis, as the images are immediately perceived by the driver; both, as a consequence, fail to measure instantaneous shifts of attention in the driver's visual search and scanning process, as directed to threat/hazard identification, and this aspect of performance as manifested under the actual conditions of driving cannot be precisely monitored and recorded. This, in turn, severely limits the ability to provide accurate feedback about deficits in a driver's search and scanning process, and to identify appropriate remedial strategies. All categories are limited in the specificity with which feedback about a driver's search and scanning performance and performance errors can be provided.
The present invention will overcome the noted limitations by utilizing proprietary computer software and commercially available, off-the-shelf hardware to implement a tabletop system. This system will provide the user with dynamic and realistic views of actual driving scenes; a means of tracking and scoring the user's skill in performing visual searching, identifying objects associated with traffic hazards or threats, switching attention from one object to another according to their instantaneous priority as hazards or threats relative to other objects visible in the driving scene, on a continuous basis; and a means of providing feedback that identifies the type, location, and timing of driver errors in search and scanning performance. Together, these system capabilities will permit assessment and training in expert search and scanning skills, an entirely new and relevant measure of driver performance that was not possible using earlier devices.